full2011_inter.pdf - page 330

2011 International Conference on Alternative Energy in Developing Countries and Emerging Economies
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Both the Thailand and Malaysia land use mapping data
are reclassified in ArcGIS with the Anemoscope
vegetation cover classification index which is converted
into corresponding roughness values during the
simulations. The land use data is then merged into one
large raster file with 90 m by 90 m pixels encompassing
the entire region studied. Table II shows the Anemoscope
vegetation cover classification index and the
corresponding roughness height, as used in the
computation of the wind resource maps.
Fig. 5 shows the roughness height data of Nakhon Si
Thammarat and Songkhla Provinces, as used in the
computation of the wind resource maps. As can be seen
from Fig. 5, most of the provinces have a roughness
height between 0.3 to 0.5, which corresponds to some
sort of mixed forest and agricultural cover. Furthermore,
there are significant forest areas where the roughness
height is above 0.85. Finally, the eastern areas of Nakhon
Si Thammarat and Songkhla Provinces have a roughness
height of 0.001 to 0.1, which corresponds to agriculture
or aquaculture zones.
Fig. 5. Roughness height of Nakhon Si Thammarat and Songkhla
provinces.
III. RESULT AND DISCUSSION
A. Wind Resource Maps
The following figures show the wind resource maps at
40 m, 65 m, 80 m, and 100 m elevations a.g.l. for Nakhon
Si Thammarat and Songkhla provinces, Thailand, Fig. 6,
7, 8, and 9, respectively.
B. Validation
In order to validate the wind resource maps of Nakhon
Si Thammarat and Songkhla provinces, results of the
simulation were compared to previous low resolution
wind atlas, other previous studies [17], and with available
wind data distributed throughout the territory. To this
end, the simulation results were compared to
observational wind speeds at 40 m a.g.l. from 10 met
stations, having a full two years of record, along the coast
of both Nakhon Si Thammarat and Songkhla Provinces.
The geographical locations of the five met stations
located in Nakhon Si Thammarat Province are shown in
Fig. 10, while Fig. 11 shows the geographical locations of
five met station located in Songkhla province.
The wind resource maps of Thailand were produced
without any surface wind data. It is noteworthy that in
this study, the primary purpose of the stations data is for
the validation of the computed wind resource maps. As a
result, uncertainty is critical since an error in the met
tower data could lead to the interpretation of erroneous
model error calculations. As a consequence, it was
decided to be prudent with the comparison because of
issues pertaining to the verification of the met stations
data and to the complexity of the terrain at the met station
locations, i.e. coastal areas.
Table III shows the results of the comparison of the
mean wind speeds observed at the 10 met stations along
with the wind speeds computed at these locations.
TABLE II
LAND COVER AND ROUGHNESS H EIGHT
Index Description Roughness Height
1 Water 0.001
2 Ice 0.001
3 Inland lake 0.001
4 Evergreen needleleaf tree 1.5
5 Evergreen broadleaf tree 3.5
6 Deciduous needleleaf tree 1.0
7 Deciduous broadleaf tree 2.0
8 Tropical broadleaf tree 3.0
9 Drought deciduous tree 0.8
10 Evergreen broadleaf shrub 0.05
11 Deciduous shrub 0.15
12 Thorn shrub 0.15
13 Short grass and forbs 0.02
14 Long grass 0.08
15 Arable land 0.08
16 Rice field 0.08
17 Sugar cane field 0.35
18 Maize field 0.25
19 Cotton field 0.1
20 Irrigated crop 0.08
21 Urban area 1.35
22 Tundra 0.01
23 Swamp 0.05
24 Soil 0.05
25 Mixed wood forest 1.5
26 Transitional forest 0.05